Real-Time Automated Interpretation of Clinical Narratives

Inactive Publication Date: 2012-11-01
CLINITHINK
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Clinicians delivering healthcare typically document progress, findings, plans, and decisions in the form of textual notes or reports (i.e., clinical narratives) in a patient record of some kind The language used to create these clinical narratives is rich, complex, and specialized.
The linguistic subtleties and complexity of clinical language make it difficult to meaningfully interpret clinical narratives in an autom

Method used

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  • Real-Time Automated Interpretation of Clinical Narratives
  • Real-Time Automated Interpretation of Clinical Narratives
  • Real-Time Automated Interpretation of Clinical Narratives

Examples

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example narratives

4. Example Narratives

[0163]To illustrate the concept and the power of the CLiX platform, we next provide examples of clinical narratives and how they are encoded by the techniques described herein. For each example, a piece of clinical narrative is provided and the output returned by the CLiXengine is shown. The screenshots represent exemplary user interfaces by clients 104 of FIG. 1.

[0164]In each screenshot, clinical narrative is entered on the right and the CLiX engine returns the corresponding SNOMED CT expression on the left in real-time. In these examples, recognized terms are underlined and highlighted in blue. The engine attempts to categorize the observations provided under familiar record headings.

4.1 Misspelling, Acronyms, Word Derivations, and Inflections

[0165]FIGS. 11A and 11B illustrate situations where the clinical narrative includes misspelled words—“cogh,”“troat,”“feverr”—as well as acronyms and word derivations such as “swollen tongue” versus “tongue swelling”. The ...

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Abstract

Techniques for enabling real-time automated interpretation of clinical narratives are disclosed. The automated interpretation can be achieved by translating narrative text into a clinical terminology-encoded structural representation such as the Systemized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) example of such a clinical terminology. The translation process enables the generation of both pre-coordinated and post-coordinated SNOMED CT concept expressions.

Description

CROSS-REFERENCE TO RELATED APPLICATION[0001]This application claims priority to U.S. Provisional Application No. 61 / 467,603, filed Mar. 25, 2011, which is incorporated herein by reference for all purposes.BACKGROUND[0002]Embodiments of this invention relate in general to natural language processing, and in particular to techniques for interpreting clinical narratives.[0003]Clinicians delivering healthcare typically document progress, findings, plans, and decisions in the form of textual notes or reports (i.e., clinical narratives) in a patient record of some kind The language used to create these clinical narratives is rich, complex, and specialized. Clinical narratives are often described as semi-structured—neither random nor easily predictable. Very subtle changes in the word content of a clinical narrative can have a dramatic effect on meaning; for example, “evidence of malignancy was found” versus “no evidence of malignancy was found.”[0004]The linguistic subtleties and complexi...

Claims

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Application Information

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IPC IPC(8): G06Q50/24G06F40/00G16H10/60
CPCG06Q10/10G06Q50/22G06F19/3487G06F17/2872G06F17/2785G16H10/60G16H15/00G06F40/30G06F40/55
Inventor JOHNSON, PETER
Owner CLINITHINK
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